AI-augmented or legacy technologies

With the regulatory environment around AI still evolving, it’s natural to wonder whether it’s better to embrace AI now or stick with what you know – your reliable legacy systems – until there’s more clarity.

After all, your financial institution's business model has been built around legacy software systems for years.

They’re comfortable, reliable, and have served your organization well. But in today’s financial services landscape, sticking with what’s familiar may not be enough to stay competitive. There’s a fine line between staying in your comfort zone and missing out on technology that could push your organization ahead. This raises an important question: Is AI a bleeding-edge risk, or is it leading-edge innovation that could drive your success?

Let’s explore a few key areas to consider when deciding whether to evolve or stick with legacy systems for now.

Aligning with Your Business Objectives

Start by examining your strategic goals.

Are you looking to tackle challenges like reducing payment fraud or minimizing false positives to enhance the accountholder experience? AI-augmented technologies can help you achieve these objectives. Think: AI-powered fraud detection systems can reduce manual efforts while significantly improving fraud detection rates – which is probably why 69% of organizations are already using AI or machine learning for fraud detection and prevention.¹

On the other hand, if your focus is on other projects that don’t yet require AI intervention, sticking with legacy technology might make more sense for now.

Maintaining a Competitive Position

In today’s competitive market, differentiating your services matters more than ever.

If you want to stay ahead, implementing AI-augmented solutions can give you a competitive edge by streamlining communications with accountholders and enhancing their experiences. For example, AI can help reduce friction in your processes and offer faster turnaround times by using generative AI to connect more easily with your non-English speaking accountholders, ultimately expanding your market reach.  

However, if you’re more comfortable following established trends rather than leading, waiting until AI becomes more widespread could be an equitable route.

Identifying Operational Efficiencies

AI-driven automation offers the opportunity to create efficiencies that let your staff members focus on higher-value work. AI can take over repetitive tasks, freeing your team to provide more personalized service. This is especially important in manual processes where AI can reduce the risk of human error and increase accuracy. The latest financial projects from Accenture indicate the gains over the next three years will be substantial for early adopters of AI: 22% – 30% productivity improvement.²

If you can pinpoint areas where AI can enhance efficiency, it may be worth taking the plunge now.

Prioritizing Change

Deciding whether to adopt AI depends largely on whether the opportunity cost of maintaining your current systems is too high.

Sticking with legacy systems might allow you to focus on other pressing priorities. However, the longer you delay, the more your financial institution might fall behind in terms of technology and service offerings. According to a World Retail Banking Report, 95% of top global banking executives said outdated legacy systems and core banking platforms inhibit efforts to optimize data and customer-centric growth strategies.³

A good starting point is for your team to assess potential gains in efficiency, experience improvements, or fraud reduction.

This will help you determine if now is the time to start integrating AI tools.

Skillset Readiness

Many AI-enabled systems today require little to no specialized knowledge to get started.

Still, it’s essential to understand whether your financial institution has the resources and expertise to implement and maintain these systems effectively. Will you need to upskill your staff, or are the AI tools you’re considering straightforward enough to integrate into your existing workflows?

Assessing your team’s readiness is a crucial step before making a decision.

Evaluating Financial and Operational Impacts

Yes, new technologies come with costs – but what’s the bigger picture?

AI-powered tools can reduce hours of manual work, increase employee retention by allowing them to focus on meaningful tasks, and reduce fraud losses. In fact, a study by Accenture found that implementing AI in the financial services industry could lead to a 6% increase in revenue.⁴

Balancing the financial costs with the potential savings in time and operational efficiency can help you determine whether to stay with legacy systems or upgrade your tech stack.

The Bottom Line

There’s no one-size-fits-all answer to when your financial institution should implement AI.

It’s about examining your goals, your current position, and the areas where AI could make the most impact. If you decide to move forward with AI, start by asking the right questions and weighing the benefits and risks so you can craft a thoughtful plan that sets you up for long-term success.

sources
¹ Trustworthy Use of Artificial Intelligence in Finance, Deloitte, accessed October 22, 2024.
² The Age of AI: Banking’s New Reality, Accenture, accessed October 22, 2024.
³ World Retail Banking Report 2022: Incumbent Banks Must Embrace Data-Centric Capabilities to Drive Personalized Customer Experiences, Capgemini, accessed October 24, 2024.
⁴ Banking on AI: Banking Top 10 Trends for 2024, Accenture, accessed October 24, 2024.